Soft Computing and Fractal Theory for Intelligent Manufacturing

1. Front Matter

   Pages i-xiv

   PDF

2. Introduction

   • Oscar Castillo, Patricia Melin

   Pages 1-4

3. Type-1 Fuzzy Logic

   • Oscar Castillo, Patricia Melin

   Pages 5-31

4. Type-2 Fuzzy Logic

   • Oscar Castillo, Patricia Melin

   Pages 33-46

5. Supervised Learning Neural Networks

   • Oscar Castillo, Patricia Melin

   Pages 47-73

6. Unsupervised Learning Neural Networks

   • Oscar Castillo, Patricia Melin

   Pages 75-92

7. Genetic Algorithms and Simulated Annealing

   • Oscar Castillo, Patricia Melin

   Pages 93-125

8. Dynamical Systems Theory

   • Oscar Castillo, Patricia Melin

   Pages 127-149

9. Plant Monitoring and Diagnostics

   • Oscar Castillo, Patricia Melin

   Pages 151-165

10. Adaptive Control of Non-Linear Plants

    • Oscar Castillo, Patricia Melin

    Pages 167-184

11. Automated Quality Control in Sound Speaker Manufacturing

    • Oscar Castillo, Patricia Melin

    Pages 185-206

12. Intelligent Manufacturing of Television Sets

    • Oscar Castillo, Patricia Melin

    Pages 207-225

13. Intelligent Manufacturing of Batteries

    • Oscar Castillo, Patricia Melin

    Pages 227-266

14. Back Matter

    Pages 267-283

    PDF

We describe in this book, new methods for intelligent manufacturing using soft computing techniques and fractal theory. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems. Fractal theory provides us with the mathematical tools to understand the geometrical complexity of natural objects and can be used for identification and modeling purposes. Combining SC techniques with fractal theory, we can take advantage of the "intelligence" provided by the computer methods and also take advantage of the descriptive power of the fractal mathematical tools. Industrial manufacturing systems can be considered as non-linear dynamical systems, and as a consequence can have highly complex dynamic behaviors. For this reason, the need for computational intelligence in these manufacturing systems has now been well recognized. We consider in this book the concept of "intelligent manufacturing" as the application of soft computing techniques and fractal theory for achieving the goals of manufacturing, which are production planning and control, monitoring and diagnosis of faults, and automated quality control. As a prelude, we provide a brief overview of the existing methodologies in Soft Computing. We then describe our own approach in dealing with the problems in achieving intelligent manufacturing. Our particular point of view is that to really achieve intelligent manufacturing in real-world applications we need to use SC techniques and fractal theory.

• Signal
• Simulation
• algorithm
• dynamische Systeme
• fractal theory
• fuzzy control
• fuzzy logic
• fuzzy system
• genetic algorithms
• intelligent manufacturing
• learning
• modeling
• neural networks
• optimization
• soft computing
• complexity

• Department of Computer Science, Tijuana Institute of Technology, Chula Vista, USA

  Oscar Castillo, Patricia Melin

• Tijuana, B. C., Mexico

  Oscar Castillo, Patricia Melin

Policies and ethics